Credit Acceptance Corporation
San Francisco, California
At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Credit Acceptance makes vehicle ownership possible for consumers other lenders decline, through a dealer network, an originations and servicing platform, and pricing and decisioning models refined over decades. The technology estate underneath this business was built project by project over a long period, and modernizing it is the largest engineering opportunity at the company. As the Distinguished Engineer, you are the senior-most individual contributor in Technology, reporting directly to the Chief Technology Officer. You will set the multi-year technical strategy for the company while staying close enough to the code and systems to remain credible - this is not an architect role that reviews designs from a distance, nor a strong engineer role that goes deep in a single domain. Two things sit at the center of the job: the target architecture for the enterprise, and the architecture for running AI agents across it. You will not own a team; you will own the hardest technical problems the company has, and get them resolved by convincing the people who do own the teams. Outcomes and Activities Enterprise target architecture: Convene the principal and staff engineers who own each domain to define the end-state architecture across originations, servicing, marketplace, data, and AI, and use it to drive the multi-year plan. Ensure every component has a defined interface with stated inputs and outputs, every unmade decision has a written principle standing in for it, and the document states honestly how close the organization is to the end state. Publish the architecture, including the tradeoffs that were rejected and why. Agentic AI architecture across the enterprise: Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, built on one common foundation rather than one stack per team. Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer. Define an identity and authorization model that treats an agent as a first-class actor with its own least-privilege entitlements, along with observability, evaluation, and cost controls that work consistently for every agent. Set policy on what an agent may decide independently versus what stays with a person, and define where that line moves and on what evidence. Design the architecture to produce an examiner-ready record of what each agent saw, recommended, and touched, and set the evaluation and adversarial testing approach that makes agent outcomes defensible. Ensure the same foundation and controls apply to agents built by outside firms on the company's behalf. Migration off on-premises infrastructure: Own the technical strategy for migrating transactional and analytical workloads off on-premises infrastructure to the company's strategic targets - AWS for transactional workloads and Databricks for analytical workloads - determining what lifts and shifts, what replatforms, what gets re-architected on the way versus after, and what the steady-state cost looks like. Own the resilience and recovery architecture for the target state. Data platform architecture: Set the architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency, moving the organization from largely batch analytical data movement to real time. Help settle the open question of who owns the transactional and analytical data models. Real-time decisioning, model serving, and experimentation: Architect for pricing and credit model and scorecard updates that drop in as a layer rather than requiring a multi-quarter rebuild, and for an experimentation platform that supports orders of magnitude more concurrent experiments than a conventional release process allows. Marketplace and search architecture: Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform, ensuring the data model supports more than one class of seller from the start. AI-native engineering practice: Define the golden path for how software is specified, generated, reviewed, tested, and deployed, including the analyzers and gates that enforce it, and measure the inputs to that practice rather than just the outputs. Hold the build-versus-buy bar for AI capability, building what is core competency and about to scale, and renting the rest. Performance and peak readiness: Own the instrumentation, baseline, and remediation architecture needed to meet the standard that no page takes more than one second. Own peak-event headroom, including understanding the limits of each system and maintaining tested degradation levers ahead of need. Operating approach: Move the organization from project-shaped systems toward owned platforms with stated contracts. Document every component's inputs and outputs, and be ready to argue why closely coupled components should not be consolidated into one. Work toward a two-week requirement-to-production iteration bar, treating architecture that cannot be delivered incrementally as unfinished. Name what comes off the plan whenever a change in direction is requested. Make the call and own the outcome on architectural recommendations. Treat security, privacy, auditability, and regulatory obligation as design inputs from the start in this regulated environment. Hands-on, not hands-off: This is not optional. Stay personally engaged in the technical work rather than directing it from a distance. Join design reviews, write proofs of concept, read code, and engage in incident analysis. This hands-on time does not replace the work the teams own, and it is not a fallback when delivery slips. Every engineer in the organization will read how you write, how you argue a design, how you handle being wrong, and how you treat engineers who disagree with you as the bar. Staff and principal engineers should be measurably better at this work for having worked with you. Success measures: A published target architecture the domain owners agree with and that the annual and long-range plans are actually written against; an enterprise agent foundation that internal teams and partners build on, with access controls, evaluation, and audit records in place; a credible, dated, costed migration path off on-premises infrastructure and demonstrated progress against it; measured improvement in chosen input metrics such as latency, availability, recovery objectives, deployment frequency, and experiment throughput; growth in the number of principal and staff engineers who are better at this work as a result of this role; and architectural decisions that stop being relitigated because the reasoning was written down and the interfaces were clear. Competencies Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience Minimum 10 years of software engineering experience or comparable depth of experience A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line. Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications. Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated . click apply for full job details
11/14/2026
Full time
At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Credit Acceptance makes vehicle ownership possible for consumers other lenders decline, through a dealer network, an originations and servicing platform, and pricing and decisioning models refined over decades. The technology estate underneath this business was built project by project over a long period, and modernizing it is the largest engineering opportunity at the company. As the Distinguished Engineer, you are the senior-most individual contributor in Technology, reporting directly to the Chief Technology Officer. You will set the multi-year technical strategy for the company while staying close enough to the code and systems to remain credible - this is not an architect role that reviews designs from a distance, nor a strong engineer role that goes deep in a single domain. Two things sit at the center of the job: the target architecture for the enterprise, and the architecture for running AI agents across it. You will not own a team; you will own the hardest technical problems the company has, and get them resolved by convincing the people who do own the teams. Outcomes and Activities Enterprise target architecture: Convene the principal and staff engineers who own each domain to define the end-state architecture across originations, servicing, marketplace, data, and AI, and use it to drive the multi-year plan. Ensure every component has a defined interface with stated inputs and outputs, every unmade decision has a written principle standing in for it, and the document states honestly how close the organization is to the end state. Publish the architecture, including the tradeoffs that were rejected and why. Agentic AI architecture across the enterprise: Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, built on one common foundation rather than one stack per team. Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer. Define an identity and authorization model that treats an agent as a first-class actor with its own least-privilege entitlements, along with observability, evaluation, and cost controls that work consistently for every agent. Set policy on what an agent may decide independently versus what stays with a person, and define where that line moves and on what evidence. Design the architecture to produce an examiner-ready record of what each agent saw, recommended, and touched, and set the evaluation and adversarial testing approach that makes agent outcomes defensible. Ensure the same foundation and controls apply to agents built by outside firms on the company's behalf. Migration off on-premises infrastructure: Own the technical strategy for migrating transactional and analytical workloads off on-premises infrastructure to the company's strategic targets - AWS for transactional workloads and Databricks for analytical workloads - determining what lifts and shifts, what replatforms, what gets re-architected on the way versus after, and what the steady-state cost looks like. Own the resilience and recovery architecture for the target state. Data platform architecture: Set the architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency, moving the organization from largely batch analytical data movement to real time. Help settle the open question of who owns the transactional and analytical data models. Real-time decisioning, model serving, and experimentation: Architect for pricing and credit model and scorecard updates that drop in as a layer rather than requiring a multi-quarter rebuild, and for an experimentation platform that supports orders of magnitude more concurrent experiments than a conventional release process allows. Marketplace and search architecture: Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform, ensuring the data model supports more than one class of seller from the start. AI-native engineering practice: Define the golden path for how software is specified, generated, reviewed, tested, and deployed, including the analyzers and gates that enforce it, and measure the inputs to that practice rather than just the outputs. Hold the build-versus-buy bar for AI capability, building what is core competency and about to scale, and renting the rest. Performance and peak readiness: Own the instrumentation, baseline, and remediation architecture needed to meet the standard that no page takes more than one second. Own peak-event headroom, including understanding the limits of each system and maintaining tested degradation levers ahead of need. Operating approach: Move the organization from project-shaped systems toward owned platforms with stated contracts. Document every component's inputs and outputs, and be ready to argue why closely coupled components should not be consolidated into one. Work toward a two-week requirement-to-production iteration bar, treating architecture that cannot be delivered incrementally as unfinished. Name what comes off the plan whenever a change in direction is requested. Make the call and own the outcome on architectural recommendations. Treat security, privacy, auditability, and regulatory obligation as design inputs from the start in this regulated environment. Hands-on, not hands-off: This is not optional. Stay personally engaged in the technical work rather than directing it from a distance. Join design reviews, write proofs of concept, read code, and engage in incident analysis. This hands-on time does not replace the work the teams own, and it is not a fallback when delivery slips. Every engineer in the organization will read how you write, how you argue a design, how you handle being wrong, and how you treat engineers who disagree with you as the bar. Staff and principal engineers should be measurably better at this work for having worked with you. Success measures: A published target architecture the domain owners agree with and that the annual and long-range plans are actually written against; an enterprise agent foundation that internal teams and partners build on, with access controls, evaluation, and audit records in place; a credible, dated, costed migration path off on-premises infrastructure and demonstrated progress against it; measured improvement in chosen input metrics such as latency, availability, recovery objectives, deployment frequency, and experiment throughput; growth in the number of principal and staff engineers who are better at this work as a result of this role; and architectural decisions that stop being relitigated because the reasoning was written down and the interfaces were clear. Competencies Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience Minimum 10 years of software engineering experience or comparable depth of experience A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line. Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications. Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated . click apply for full job details
Pay Range: $50.00hr - $55.00hr Job Overview: As a Consulting Data Engineer, the successful candidate will architect, build, and optimize the next generation of real-time healthcare data platforms and event-driven architectures. The candidate will play a foundational role in moving clinical, operational, and financial data away from legacy batch processing toward high-throughput, near-zero-latency streaming pipelines. In this role, the candidate will champion modern data engineering practices, design highly scalable cloud-native pipelines, and mentor a growing team of engineers. The candidate will bridge the gap between complex electronic health records (EHR) and data consumers-enabling data scientists, software engineers, and clinical analysts to securely access, stream, and query compliant data at scale to improve patient outcomes and operational efficiency. Core Responsibilities: Architect Real-Time Pipelines: Design, implement, and monitor high-throughput, fault-tolerant streaming pipelines that ingest and process millions of concurrent healthcare data events (e.g., live telemetry, HL7 feeds, ADT messages). Scale Google Cloud Infrastructure: Build and maintain scalable, secure, and cost-effective cloud data infrastructure using Google Cloud healthcare-native tools and Infrastructure as Code (IaC). Enforce Healthcare Compliance & Security: Uphold strict data security protocols (HIPAA, HITRUST, SOC2) by building robust data lakehouse architectures that enforce PHI/PII masking, role-based access control (RBAC), and encryption at rest and in transit. Enable Self-Service Data & Interoperability: Build out streaming data ecosystems that support modern healthcare interoperability, managing real-time data catalogs and schema registries. Promote Code Excellence: Write modular, highly reusable, and performance-tested code; lead code reviews and establish standardized CI/CD automated deployment workflows. Optimize Data Reliability: Set and champion strict SLAs for clinical data delivery, establish automated data-quality testing, and implement proactive system monitoring and alerting. Collaborate & Mentor: Work closely with Data Architects, Clinical Product Managers, and AI/ML teams to translate healthcare requirements into technical blueprints while mentoring mid-level engineers. Required Qualifications: 13+ years of experience in dedicated data engineering, data architecture, or distributed systems software engineering roles. 4+ years of experience specifically within the healthcare domain (payer, provider, digital health, or health tech). Google Cloud Certified Professional Data Engineer (or equivalent proven expert-level architecture experience on GCP). Advanced Event-Driven Architecture: Mastery of high-volume streaming technologies including Apache Kafka and Google Cloud Pub/Sub for decoupled, real-time message routing. Stream Processing: Deep hands-on experience with Apache Flink or Google Cloud Dataflow (Apache Beam) for real-time streaming, complex event processing (CEP), windowing, and streaming data transformations. Interoperability Standards: Deep expertise working with FHIR (Fast Healthcare Interoperability Resources) JSON structures, HL7 v2/v3 messaging, and DICOM imaging standard streams. GCP Healthcare Tools: Hands-on experience implementing and scaling the Google Cloud Healthcare API (specifically FHIR stores and HL7v2 stores). EHR Integration: Experience integrating streaming pipelines with major EHR systems (such as Epic, Cerner, or Meditech). Google Cloud Ecosystem: Technical mastery of BigQuery (including partitioning, clustering, and streaming inserts), Cloud Storage, Dataproc, and Cloud Composer (Apache Airflow). Programming Languages: Proficiency in Python, Scala, or Java, with a strong focus on writing optimized code for distributed computing platforms (like Spark or Beam). Modern Data Stack & Modeling: Mastery of modern analytics engineering frameworks (such as dbt), dimensional data modeling, and lakehouse architectures (e.g., Iceberg, Delta Lake). DevOps & Automation: Robust experience building automated CI/CD pipelines (GitHub Actions, GitLab CI) and managing infrastructure using Terraform. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
11/14/2026
Full time
Pay Range: $50.00hr - $55.00hr Job Overview: As a Consulting Data Engineer, the successful candidate will architect, build, and optimize the next generation of real-time healthcare data platforms and event-driven architectures. The candidate will play a foundational role in moving clinical, operational, and financial data away from legacy batch processing toward high-throughput, near-zero-latency streaming pipelines. In this role, the candidate will champion modern data engineering practices, design highly scalable cloud-native pipelines, and mentor a growing team of engineers. The candidate will bridge the gap between complex electronic health records (EHR) and data consumers-enabling data scientists, software engineers, and clinical analysts to securely access, stream, and query compliant data at scale to improve patient outcomes and operational efficiency. Core Responsibilities: Architect Real-Time Pipelines: Design, implement, and monitor high-throughput, fault-tolerant streaming pipelines that ingest and process millions of concurrent healthcare data events (e.g., live telemetry, HL7 feeds, ADT messages). Scale Google Cloud Infrastructure: Build and maintain scalable, secure, and cost-effective cloud data infrastructure using Google Cloud healthcare-native tools and Infrastructure as Code (IaC). Enforce Healthcare Compliance & Security: Uphold strict data security protocols (HIPAA, HITRUST, SOC2) by building robust data lakehouse architectures that enforce PHI/PII masking, role-based access control (RBAC), and encryption at rest and in transit. Enable Self-Service Data & Interoperability: Build out streaming data ecosystems that support modern healthcare interoperability, managing real-time data catalogs and schema registries. Promote Code Excellence: Write modular, highly reusable, and performance-tested code; lead code reviews and establish standardized CI/CD automated deployment workflows. Optimize Data Reliability: Set and champion strict SLAs for clinical data delivery, establish automated data-quality testing, and implement proactive system monitoring and alerting. Collaborate & Mentor: Work closely with Data Architects, Clinical Product Managers, and AI/ML teams to translate healthcare requirements into technical blueprints while mentoring mid-level engineers. Required Qualifications: 13+ years of experience in dedicated data engineering, data architecture, or distributed systems software engineering roles. 4+ years of experience specifically within the healthcare domain (payer, provider, digital health, or health tech). Google Cloud Certified Professional Data Engineer (or equivalent proven expert-level architecture experience on GCP). Advanced Event-Driven Architecture: Mastery of high-volume streaming technologies including Apache Kafka and Google Cloud Pub/Sub for decoupled, real-time message routing. Stream Processing: Deep hands-on experience with Apache Flink or Google Cloud Dataflow (Apache Beam) for real-time streaming, complex event processing (CEP), windowing, and streaming data transformations. Interoperability Standards: Deep expertise working with FHIR (Fast Healthcare Interoperability Resources) JSON structures, HL7 v2/v3 messaging, and DICOM imaging standard streams. GCP Healthcare Tools: Hands-on experience implementing and scaling the Google Cloud Healthcare API (specifically FHIR stores and HL7v2 stores). EHR Integration: Experience integrating streaming pipelines with major EHR systems (such as Epic, Cerner, or Meditech). Google Cloud Ecosystem: Technical mastery of BigQuery (including partitioning, clustering, and streaming inserts), Cloud Storage, Dataproc, and Cloud Composer (Apache Airflow). Programming Languages: Proficiency in Python, Scala, or Java, with a strong focus on writing optimized code for distributed computing platforms (like Spark or Beam). Modern Data Stack & Modeling: Mastery of modern analytics engineering frameworks (such as dbt), dimensional data modeling, and lakehouse architectures (e.g., Iceberg, Delta Lake). DevOps & Automation: Robust experience building automated CI/CD pipelines (GitHub Actions, GitLab CI) and managing infrastructure using Terraform. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
Pay Range: $50.00hr - $55.00hr Job Overview: As a Consulting Data Engineer, the successful candidate will architect, build, and optimize the next generation of real-time healthcare data platforms and event-driven architectures. The candidate will play a foundational role in moving clinical, operational, and financial data away from legacy batch processing toward high-throughput, near-zero-latency streaming pipelines. In this role, the candidate will champion modern data engineering practices, design highly scalable cloud-native pipelines, and mentor a growing team of engineers. The candidate will bridge the gap between complex electronic health records (EHR) and data consumers-enabling data scientists, software engineers, and clinical analysts to securely access, stream, and query compliant data at scale to improve patient outcomes and operational efficiency. Core Responsibilities: Architect Real-Time Pipelines: Design, implement, and monitor high-throughput, fault-tolerant streaming pipelines that ingest and process millions of concurrent healthcare data events (e.g., live telemetry, HL7 feeds, ADT messages). Scale Google Cloud Infrastructure: Build and maintain scalable, secure, and cost-effective cloud data infrastructure using Google Cloud healthcare-native tools and Infrastructure as Code (IaC). Enforce Healthcare Compliance & Security: Uphold strict data security protocols (HIPAA, HITRUST, SOC2) by building robust data lakehouse architectures that enforce PHI/PII masking, role-based access control (RBAC), and encryption at rest and in transit. Enable Self-Service Data & Interoperability: Build out streaming data ecosystems that support modern healthcare interoperability, managing real-time data catalogs and schema registries. Promote Code Excellence: Write modular, highly reusable, and performance-tested code; lead code reviews and establish standardized CI/CD automated deployment workflows. Optimize Data Reliability: Set and champion strict SLAs for clinical data delivery, establish automated data-quality testing, and implement proactive system monitoring and alerting. Collaborate & Mentor: Work closely with Data Architects, Clinical Product Managers, and AI/ML teams to translate healthcare requirements into technical blueprints while mentoring mid-level engineers. Required Qualifications: 13+ years of experience in dedicated data engineering, data architecture, or distributed systems software engineering roles. 4+ years of experience specifically within the healthcare domain (payer, provider, digital health, or health tech). Google Cloud Certified Professional Data Engineer (or equivalent proven expert-level architecture experience on GCP). Advanced Event-Driven Architecture: Mastery of high-volume streaming technologies including Apache Kafka and Google Cloud Pub/Sub for decoupled, real-time message routing. Stream Processing: Deep hands-on experience with Apache Flink or Google Cloud Dataflow (Apache Beam) for real-time streaming, complex event processing (CEP), windowing, and streaming data transformations. Interoperability Standards: Deep expertise working with FHIR (Fast Healthcare Interoperability Resources) JSON structures, HL7 v2/v3 messaging, and DICOM imaging standard streams. GCP Healthcare Tools: Hands-on experience implementing and scaling the Google Cloud Healthcare API (specifically FHIR stores and HL7v2 stores). EHR Integration: Experience integrating streaming pipelines with major EHR systems (such as Epic, Cerner, or Meditech). Google Cloud Ecosystem: Technical mastery of BigQuery (including partitioning, clustering, and streaming inserts), Cloud Storage, Dataproc, and Cloud Composer (Apache Airflow). Programming Languages: Proficiency in Python, Scala, or Java, with a strong focus on writing optimized code for distributed computing platforms (like Spark or Beam). Modern Data Stack & Modeling: Mastery of modern analytics engineering frameworks (such as dbt), dimensional data modeling, and lakehouse architectures (e.g., Iceberg, Delta Lake). DevOps & Automation: Robust experience building automated CI/CD pipelines (GitHub Actions, GitLab CI) and managing infrastructure using Terraform. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
11/14/2026
Full time
Pay Range: $50.00hr - $55.00hr Job Overview: As a Consulting Data Engineer, the successful candidate will architect, build, and optimize the next generation of real-time healthcare data platforms and event-driven architectures. The candidate will play a foundational role in moving clinical, operational, and financial data away from legacy batch processing toward high-throughput, near-zero-latency streaming pipelines. In this role, the candidate will champion modern data engineering practices, design highly scalable cloud-native pipelines, and mentor a growing team of engineers. The candidate will bridge the gap between complex electronic health records (EHR) and data consumers-enabling data scientists, software engineers, and clinical analysts to securely access, stream, and query compliant data at scale to improve patient outcomes and operational efficiency. Core Responsibilities: Architect Real-Time Pipelines: Design, implement, and monitor high-throughput, fault-tolerant streaming pipelines that ingest and process millions of concurrent healthcare data events (e.g., live telemetry, HL7 feeds, ADT messages). Scale Google Cloud Infrastructure: Build and maintain scalable, secure, and cost-effective cloud data infrastructure using Google Cloud healthcare-native tools and Infrastructure as Code (IaC). Enforce Healthcare Compliance & Security: Uphold strict data security protocols (HIPAA, HITRUST, SOC2) by building robust data lakehouse architectures that enforce PHI/PII masking, role-based access control (RBAC), and encryption at rest and in transit. Enable Self-Service Data & Interoperability: Build out streaming data ecosystems that support modern healthcare interoperability, managing real-time data catalogs and schema registries. Promote Code Excellence: Write modular, highly reusable, and performance-tested code; lead code reviews and establish standardized CI/CD automated deployment workflows. Optimize Data Reliability: Set and champion strict SLAs for clinical data delivery, establish automated data-quality testing, and implement proactive system monitoring and alerting. Collaborate & Mentor: Work closely with Data Architects, Clinical Product Managers, and AI/ML teams to translate healthcare requirements into technical blueprints while mentoring mid-level engineers. Required Qualifications: 13+ years of experience in dedicated data engineering, data architecture, or distributed systems software engineering roles. 4+ years of experience specifically within the healthcare domain (payer, provider, digital health, or health tech). Google Cloud Certified Professional Data Engineer (or equivalent proven expert-level architecture experience on GCP). Advanced Event-Driven Architecture: Mastery of high-volume streaming technologies including Apache Kafka and Google Cloud Pub/Sub for decoupled, real-time message routing. Stream Processing: Deep hands-on experience with Apache Flink or Google Cloud Dataflow (Apache Beam) for real-time streaming, complex event processing (CEP), windowing, and streaming data transformations. Interoperability Standards: Deep expertise working with FHIR (Fast Healthcare Interoperability Resources) JSON structures, HL7 v2/v3 messaging, and DICOM imaging standard streams. GCP Healthcare Tools: Hands-on experience implementing and scaling the Google Cloud Healthcare API (specifically FHIR stores and HL7v2 stores). EHR Integration: Experience integrating streaming pipelines with major EHR systems (such as Epic, Cerner, or Meditech). Google Cloud Ecosystem: Technical mastery of BigQuery (including partitioning, clustering, and streaming inserts), Cloud Storage, Dataproc, and Cloud Composer (Apache Airflow). Programming Languages: Proficiency in Python, Scala, or Java, with a strong focus on writing optimized code for distributed computing platforms (like Spark or Beam). Modern Data Stack & Modeling: Mastery of modern analytics engineering frameworks (such as dbt), dimensional data modeling, and lakehouse architectures (e.g., Iceberg, Delta Lake). DevOps & Automation: Robust experience building automated CI/CD pipelines (GitHub Actions, GitLab CI) and managing infrastructure using Terraform. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
11/14/2026
Full time
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
11/14/2026
Full time
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
11/14/2026
Full time
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
Job Description Intellibus designs and engineers platforms trusted by some of the most established FinTech and financial trading firms in the world. Our engineering teams build systems that power high-volume trading, real-time financial data, and mission-critical infrastructure. We expect our engineers to operate at a level where technical depth, sound judgment, and clear communication all carry weight - the problems are complex, the systems are production-critical, and the people you work with will hold you to a high standard. The Staff Engineer Role We are hiring a Staff Engineer to design, build, and own full-stack systems powering financial platforms - from frontend architecture to backend services to distributed event-driven infrastructure. This is not a role where you pick up tickets and ship features. You will be expected to think end-to-end: to understand the business problem, design the system, make the trade-offs, and deliver production-grade software that performs reliably under heavy load. You will work directly with senior stakeholders across technical and non-technical functions, often navigating competing priorities, ambiguity, and high-pressure timelines. The ability to communicate clearly, manage complexity across people and systems, and maintain a high quality bar when things get difficult is essential. If you have built and shipped systems that mattered - at a startup, at a large company, or somewhere in between - and you are looking for a role where you will be challenged technically while also growing your ability to operate in complex, high-stakes environments, we want to hear from you. What You Will Do Frontend Architecture Build scalable frontend platforms using React, Next.js, and TypeScript. Design modern UI architectures: server-side rendering, component-driven design, performance optimization, and state management patterns. Develop reusable component systems and scalable frontend frameworks. Backend Engineering Build backend services using Node.js and NestJS. Design and implement REST APIs, microservices, asynchronous workflows, and high-performance data processing systems. Work with SQL and NoSQL databases using TypeORM, and optimize for throughput and reliability. Event-Driven & Distributed Systems Design distributed systems built on event-driven architecture using Kafka, Azure Service Bus, Azure Event Grid, and messaging/queue systems. Build services that process high-volume financial events and real-time trading data. Cloud & Infrastructure Deploy and operate systems on Microsoft Azure, including Azure App Services, Azure Data Fabric, messaging platforms, Docker, CI/CD pipelines, and Linux environments. Design infrastructure that supports resilient, scalable distributed systems. What Sets You Apart We are looking for engineers who demonstrate several of the following: You have designed and operated event-driven distributed systems that process high-volume real-time data. You have a deep understanding of algorithms, data structures, and time complexity - and you apply that understanding to build systems, not just pass interviews. You have built full-stack platforms using React/Next.js and Node.js/NestJS that run reliably in production. You have hands-on experience with message queues, streaming platforms, and asynchronous workflows - Kafka, Azure Service Bus, BullMQ, or similar. You reason clearly about system trade-offs: latency vs. throughput, consistency vs. availability, speed vs. reliability. You have operated systems in cloud environments like Microsoft Azure, including debugging production incidents and improving performance under pressure. You design systems end-to-end and take ownership of architecture and production outcomes - not just the code you wrote. You have mentored other engineers and contributed to architecture reviews, engineering standards, and technical decision-making. You communicate well under pressure. You can hold your ground in a room full of stakeholders, explain a technical decision to a non-technical audience, and navigate situations where the right path forward is not obvious. Technology Ecosystem Frontend: React, Next.js, TypeScript, JavaScript, TailwindCSS, HTML5, CSS3 Backend: Node.js, NestJS, REST APIs, Microservices, BullMQ, TypeORM Event-Driven: Kafka, Azure Service Bus, Azure Event Grid Infrastructure: Microsoft Azure, Azure Data Fabric, Docker, CI/CD, Infrastructure-as-Code, Linux Data: SQL, NoSQL, Azure Data Fabric Compensation: $75 - $85 / Hour Our Process 15-minute video call with someone from our team 4 Proctored GQ Tests (under 2 hours) 30-45-minute final video interview Job offer If this sounds like the kind of work you want to be doing, apply now. Our team will be in touch within the hour.
11/14/2026
Full time
Job Description Intellibus designs and engineers platforms trusted by some of the most established FinTech and financial trading firms in the world. Our engineering teams build systems that power high-volume trading, real-time financial data, and mission-critical infrastructure. We expect our engineers to operate at a level where technical depth, sound judgment, and clear communication all carry weight - the problems are complex, the systems are production-critical, and the people you work with will hold you to a high standard. The Staff Engineer Role We are hiring a Staff Engineer to design, build, and own full-stack systems powering financial platforms - from frontend architecture to backend services to distributed event-driven infrastructure. This is not a role where you pick up tickets and ship features. You will be expected to think end-to-end: to understand the business problem, design the system, make the trade-offs, and deliver production-grade software that performs reliably under heavy load. You will work directly with senior stakeholders across technical and non-technical functions, often navigating competing priorities, ambiguity, and high-pressure timelines. The ability to communicate clearly, manage complexity across people and systems, and maintain a high quality bar when things get difficult is essential. If you have built and shipped systems that mattered - at a startup, at a large company, or somewhere in between - and you are looking for a role where you will be challenged technically while also growing your ability to operate in complex, high-stakes environments, we want to hear from you. What You Will Do Frontend Architecture Build scalable frontend platforms using React, Next.js, and TypeScript. Design modern UI architectures: server-side rendering, component-driven design, performance optimization, and state management patterns. Develop reusable component systems and scalable frontend frameworks. Backend Engineering Build backend services using Node.js and NestJS. Design and implement REST APIs, microservices, asynchronous workflows, and high-performance data processing systems. Work with SQL and NoSQL databases using TypeORM, and optimize for throughput and reliability. Event-Driven & Distributed Systems Design distributed systems built on event-driven architecture using Kafka, Azure Service Bus, Azure Event Grid, and messaging/queue systems. Build services that process high-volume financial events and real-time trading data. Cloud & Infrastructure Deploy and operate systems on Microsoft Azure, including Azure App Services, Azure Data Fabric, messaging platforms, Docker, CI/CD pipelines, and Linux environments. Design infrastructure that supports resilient, scalable distributed systems. What Sets You Apart We are looking for engineers who demonstrate several of the following: You have designed and operated event-driven distributed systems that process high-volume real-time data. You have a deep understanding of algorithms, data structures, and time complexity - and you apply that understanding to build systems, not just pass interviews. You have built full-stack platforms using React/Next.js and Node.js/NestJS that run reliably in production. You have hands-on experience with message queues, streaming platforms, and asynchronous workflows - Kafka, Azure Service Bus, BullMQ, or similar. You reason clearly about system trade-offs: latency vs. throughput, consistency vs. availability, speed vs. reliability. You have operated systems in cloud environments like Microsoft Azure, including debugging production incidents and improving performance under pressure. You design systems end-to-end and take ownership of architecture and production outcomes - not just the code you wrote. You have mentored other engineers and contributed to architecture reviews, engineering standards, and technical decision-making. You communicate well under pressure. You can hold your ground in a room full of stakeholders, explain a technical decision to a non-technical audience, and navigate situations where the right path forward is not obvious. Technology Ecosystem Frontend: React, Next.js, TypeScript, JavaScript, TailwindCSS, HTML5, CSS3 Backend: Node.js, NestJS, REST APIs, Microservices, BullMQ, TypeORM Event-Driven: Kafka, Azure Service Bus, Azure Event Grid Infrastructure: Microsoft Azure, Azure Data Fabric, Docker, CI/CD, Infrastructure-as-Code, Linux Data: SQL, NoSQL, Azure Data Fabric Compensation: $75 - $85 / Hour Our Process 15-minute video call with someone from our team 4 Proctored GQ Tests (under 2 hours) 30-45-minute final video interview Job offer If this sounds like the kind of work you want to be doing, apply now. Our team will be in touch within the hour.
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
11/14/2026
Full time
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
11/14/2026
Full time
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
11/14/2026
Full time
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
11/13/2026
Full time
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
11/13/2026
Full time
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
11/13/2026
Full time
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
11/13/2026
Full time
Introduction At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'll have the tools and opportunities to advance your career while creating software that changes the world. Your Role and Responsibilities About the Role: Today, enterprises stitch together separate systems for streaming, analytics, and serving. Each of these systems come with its own latency, cost, and operational overhead. The next evolution of Confluent's platform collapses that complexity by continuously materializing streaming data into fast, queryable state that serves real-time analytics, operational applications, and downstream intelligent systems from a single foundation. As a Staff Product Manager, you'll own the vision, strategy, and roadmap for the core streaming analytics engine underlying Confluent's real-time data platform. This system sits at the intersection of stream processing, real-time analytical databases, and modern serving infrastructure, continuously transforming data in motion into low-latency, queryable materialized views that power AI agents, dashboards, operational queries, and event-driven applications. You'll own the engine: the storage, materialization, query layer, and performance, while partnering with peer product managers who own the downstream product experiences built on top of it. This is a foundational, high-leverage role. You'll define a new product category that brings together concepts from streaming analytics, real-time OLAP, materialized views, and modern database systems into a cloud-native, streaming-first architecture. You'll partner directly with engineering, design, and senior leadership to bring this to market and position Confluent as a compelling alternative to standalone real-time analytical databases. What You Will Do: Own the product strategy for Confluent's streaming analytics engine: storage, materialization, query serving, performance, and developer experience. Develop competitive strategy against established real-time analytical databases, articulating Confluent's differentiated value as a streaming-native alternative. Drive key architectural and product tradeoffs across consistency, latency, query performance, cost, and developer ergonomics. Partner deeply with engineering to navigate the technical complexity of building a new cloud-native data system at scale. Collaborate with peer product managers who own downstream experiences including AI, context delivery, and application integration, to ensure the engine meets the needs of the products built on it. Work with customers and design partners to validate use cases across real-time analytics, operational applications, and AI, shaping the developer experience and refining go-to-market positioning. Collaborate with Confluent's broader product and platform teams to ensure tight integration with Kafka, Flink, and Confluent Cloud. Define success metrics, cost models, and pricing strategy for a new product area. Influence Confluent's company-wide platform strategy through executive-level communication and cross-functional leadership. Required Skills What You Will Bring: Bachelor's degree or equivalent practical experience. 8+ years of experience in product management or related technical roles. 5+ years of experience taking technical infrastructure or data products from conception to launch. Deep familiarity with real-time analytics, database internals, or streaming data platform architecture, either through product management or hands-on engineering. Experience defining and launching products in the data infrastructure, analytics database, or stream processing space. Strong technical judgment, comfortable navigating tradeoffs in distributed systems, storage engines, query performance, and cost optimization. Track record of leading cross-functional initiatives with executive-level visibility and communicating technical strategy to senior leadership. Preferred Skills Engineering background in analytical databases, stream processing, or distributed storage systems. Experience with real-time OLAP engines (e.g., ClickHouse, Apache Druid, StarRocks, Apache Pinot) as a builder, product manager, or power user. Familiarity with Kafka, Flink, or similar streaming infrastructure. Experience building products that serve AI/ML workloads for retrieval, feature serving, or context delivery. Prior experience with cloud-native infrastructure products and consumption-based pricing models. Experience working on open source data infrastructure projects. Additional Details (US) IBM offers a competitive and comprehensive benefits program. Eligible employees may have access to: - Healthcare benefits including medical & prescription drug coverage, dental, vision, and mental health & well being - Financial programs such as 401(k), cash balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short & long- term disability coverage, and opportunities for performance based salary incentive programs - Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM Policy, and other Paid Care Leave programs. IBM also offers paid family leave benefits to eligible employees where required by applicable law - Training and educational resources on our personalized, AI-driven learning platform where IBMers can grow skills and obtain industry-recognized certifications to achieve their career goals - Diverse and inclusive employee resource groups, giving & volunteer opportunities, and discounts on retail products, services & experiences We consider qualified applicants with criminal histories, consistent with applicable law. This position was posted on the date cited in the key job details section and is anticipated to remain posted for 21 days from this date or less if not needed to fill the role. Compensation, Benefits and Work Authorization The compensation range and benefits for this position are based on a full-time schedule for a full calendar year. The salary will vary depending on your job-related skills, experience and location. Pay increment and frequency of pay will be in accordance with employment classification and applicable laws. For part time roles, your compensation and benefits will be adjusted to reflect your hours. Benefits may be pro-rated for those who start working during the calendar year. IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
This job is with Colt Technology Services, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Colt provides network, voice and data centre services to thousands of businesses around the world, allowing them to focus on delivering their business goals instead of the underlying infrastructure. Summary Job title : Senior AI Engineer Reports to : VP of AI Technology and Architecture Job location : Must have ability to be onsite in Boulder, CO office for 2-3 days a week About Colt and the AI Practice Colt Technology Services is a global digital infrastructure company, operating one of the world's largest fiber networks across Europe and Asia. We are building a Boulder-based AI team as the engineering center of our AI Practice. The team is responsible for how AI is adopted, governed, and scaled across Colt. The AI Practice operates across several parallel workstreams, including use case delivery, AI WAN, and private AI. The Boulder team is where we build, test, and validate before we scale. Why we need this role This is a build role. You will take AI use cases from a business problem to something running in production and being used every day: retrieval and search over Colt's own data, agents that carry out multi-step work, and AI built into the systems Colt's teams already rely on. We are looking for a strong software engineer first. If you have spent eight to ten years building and running production systems and even if you have not yet shipped an LLM-based product, we want to hear from. The platform, the tooling, and the model access are already in place, and a staff-level AI engineer on the team will pair with you directly on the AI side of the work. The AI-specific skills you can bring to the table is a plus but is also learnable. The engineering experience and judgement that comes from having owned real systems in production is not, and that is the part we are hiring for. What we do expect is that you have already got hands on with AI, whether at work or as a side project for yourself. You will be working directly with the Colt teams taking requirements from them. The team is small by design, the problems are real, and what you build in your first year sets the pattern for how Colt builds AI. What you will do Build AI Use Cases Design and build AI applications end to end: data access, retrieval, model calls, orchestration, and the interfaces people use Work with large language models through APIs and self-hosted inference, covering prompting, tool use, retrieval, and multi-step agent workflows Build evaluation harnesses that show whether a use case is good enough to ship, and keep owning them after it ships Integrate AI into Colt's existing systems and data, within the constraints of a live enterprise environment Work Directly With the Business Work with the Colt teams, who will be your customers, and who will use what you build, across network operations, service delivery, finance, and others Turn a loosely described business problem into a scoped, buildable design Show working software early and often, and change direction when the first answer turns out to be wrong Be straight with stakeholders about what AI is not the right tool for Take It to Production and Keep It There Move your own work from prototype to production-grade: tested, instrumented, documented, and supportable Monitor accuracy, latency, and cost in production, and act when they drift Work with platform engineers on deployment, and hand over cleanly to production operations Contribute reusable patterns, components, and internal libraries so the next use case is faster than the last What we're looking for Engineering Experience: 8-10+ years building production software. You have owned systems end to end: designed them, shipped them, operated them, and been on the hook when they broke. Languages: Strong in Python, or strong in another language such as Java, Go, C#, or TypeScript and ready to work primarily in Python. Production Systems: APIs and service integration, working with real data at scale, testing, CI/CD, and debugging things that are already live in front of users. Cloud: Comfortable in any major cloud. We build primarily on Google Cloud; equivalent AWS or Azure experience is ok to start. Working Style: Comfortable with ambiguity and with direct contact with non-technical stakeholders. You ask what the problem is before deciding what to build. Hands-On with AI: You have already built something with it under your own steam. A side project, a prototype at work, an internal tool, a serious evaluation you ran, or agentic coding tools you use daily and have opinions about. It does not need to have shipped, been finished, or worked. We want to hear what you tried, what broke, and what you concluded. Helpful, Not Required: Any of this at enterprise scale: production RAG over messy real-world data, agent frameworks, evaluation tooling, Vertex AI, Kubernetes, Terraform. Useful if you have it, and teachable if you do not. HOW YOU WILL RAMP You pair with a staff-level AI engineer from your first week, on a live use case rather than a training exercise The AI platform is already running: model gateway, evaluation tooling, deployment pipelines, and sandbox, development, and production environments We expect you to put something small into real use inside your first 90 days, and to lead a use case end to end within six months WHEN WE TALK Come ready to walk us through something you have built with AI, however small or unfinished. We would rather see a rough prototype you can explain in depth than a polished project you cannot. Expect us to ask where it fell short, what you would do differently, and how you decided whether it was any good. How you evaluated it matters more to us than what you shipped. If you have not used AI tools in your own engineering work, this will be a difficult conversation. That is the one gap we are not set up to close for you. What we offer you: Looking to make a mark? At Colt, you'll make a difference. Because around here, we empower people. We don't tell you what to do. Instead, we employ people we trust, who come together across the globe to create intelligent solutions. Our global teams are full of ambitious, driven people, all working together towards one shared purpose: to put the power of the digital universe in the hands of our customers wherever, whenever and however they want. We give our people the opportunity to inspire and lead teams, and work on projects that connect people, cities, businesses, and ideas. We want you to help us change the world, for the better. Diversity and inclusion Inclusion and valuing diversity of thought and experience are at the heart of our culture here at Colt. From day one, you'll be encouraged to be yourself because we believe that's what helps our people to thrive. We welcome people with diverse backgrounds and experiences, regardless of their gender identity or expression, sexual orientation, race, religion, disability, neurodiversity, age, marital status, pregnancy status, or place of birth. Most recently we have: Signed the UN Women Empowerment Principles which guide our Gender Action Plan Trained 60 (and growing) Colties to be Mental Health First Aiders Please speak with a member of our recruitment team if you require adjustments to our recruitment process to support you. For more information about our Inclusion and Diversity agenda, visit our DEI pages . Benefits Our benefits support you through all parts of life, for both physical and mental health. Flexible working hours and the option to work from home. Extensive induction program with experienced mentors and buddies. Opportunities for further development and educational opportunities. Global Family Leave Policy. Employee Assistance Program. Internal inclusion & diversity employee networks. A global network When you join Colt you become part of our global network. We are proud of our colleagues and the stories and experience they bring - take a look at 'Our People' site including our Empowered Women in Tech.
11/13/2026
Full time
This job is with Colt Technology Services, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Colt provides network, voice and data centre services to thousands of businesses around the world, allowing them to focus on delivering their business goals instead of the underlying infrastructure. Summary Job title : Senior AI Engineer Reports to : VP of AI Technology and Architecture Job location : Must have ability to be onsite in Boulder, CO office for 2-3 days a week About Colt and the AI Practice Colt Technology Services is a global digital infrastructure company, operating one of the world's largest fiber networks across Europe and Asia. We are building a Boulder-based AI team as the engineering center of our AI Practice. The team is responsible for how AI is adopted, governed, and scaled across Colt. The AI Practice operates across several parallel workstreams, including use case delivery, AI WAN, and private AI. The Boulder team is where we build, test, and validate before we scale. Why we need this role This is a build role. You will take AI use cases from a business problem to something running in production and being used every day: retrieval and search over Colt's own data, agents that carry out multi-step work, and AI built into the systems Colt's teams already rely on. We are looking for a strong software engineer first. If you have spent eight to ten years building and running production systems and even if you have not yet shipped an LLM-based product, we want to hear from. The platform, the tooling, and the model access are already in place, and a staff-level AI engineer on the team will pair with you directly on the AI side of the work. The AI-specific skills you can bring to the table is a plus but is also learnable. The engineering experience and judgement that comes from having owned real systems in production is not, and that is the part we are hiring for. What we do expect is that you have already got hands on with AI, whether at work or as a side project for yourself. You will be working directly with the Colt teams taking requirements from them. The team is small by design, the problems are real, and what you build in your first year sets the pattern for how Colt builds AI. What you will do Build AI Use Cases Design and build AI applications end to end: data access, retrieval, model calls, orchestration, and the interfaces people use Work with large language models through APIs and self-hosted inference, covering prompting, tool use, retrieval, and multi-step agent workflows Build evaluation harnesses that show whether a use case is good enough to ship, and keep owning them after it ships Integrate AI into Colt's existing systems and data, within the constraints of a live enterprise environment Work Directly With the Business Work with the Colt teams, who will be your customers, and who will use what you build, across network operations, service delivery, finance, and others Turn a loosely described business problem into a scoped, buildable design Show working software early and often, and change direction when the first answer turns out to be wrong Be straight with stakeholders about what AI is not the right tool for Take It to Production and Keep It There Move your own work from prototype to production-grade: tested, instrumented, documented, and supportable Monitor accuracy, latency, and cost in production, and act when they drift Work with platform engineers on deployment, and hand over cleanly to production operations Contribute reusable patterns, components, and internal libraries so the next use case is faster than the last What we're looking for Engineering Experience: 8-10+ years building production software. You have owned systems end to end: designed them, shipped them, operated them, and been on the hook when they broke. Languages: Strong in Python, or strong in another language such as Java, Go, C#, or TypeScript and ready to work primarily in Python. Production Systems: APIs and service integration, working with real data at scale, testing, CI/CD, and debugging things that are already live in front of users. Cloud: Comfortable in any major cloud. We build primarily on Google Cloud; equivalent AWS or Azure experience is ok to start. Working Style: Comfortable with ambiguity and with direct contact with non-technical stakeholders. You ask what the problem is before deciding what to build. Hands-On with AI: You have already built something with it under your own steam. A side project, a prototype at work, an internal tool, a serious evaluation you ran, or agentic coding tools you use daily and have opinions about. It does not need to have shipped, been finished, or worked. We want to hear what you tried, what broke, and what you concluded. Helpful, Not Required: Any of this at enterprise scale: production RAG over messy real-world data, agent frameworks, evaluation tooling, Vertex AI, Kubernetes, Terraform. Useful if you have it, and teachable if you do not. HOW YOU WILL RAMP You pair with a staff-level AI engineer from your first week, on a live use case rather than a training exercise The AI platform is already running: model gateway, evaluation tooling, deployment pipelines, and sandbox, development, and production environments We expect you to put something small into real use inside your first 90 days, and to lead a use case end to end within six months WHEN WE TALK Come ready to walk us through something you have built with AI, however small or unfinished. We would rather see a rough prototype you can explain in depth than a polished project you cannot. Expect us to ask where it fell short, what you would do differently, and how you decided whether it was any good. How you evaluated it matters more to us than what you shipped. If you have not used AI tools in your own engineering work, this will be a difficult conversation. That is the one gap we are not set up to close for you. What we offer you: Looking to make a mark? At Colt, you'll make a difference. Because around here, we empower people. We don't tell you what to do. Instead, we employ people we trust, who come together across the globe to create intelligent solutions. Our global teams are full of ambitious, driven people, all working together towards one shared purpose: to put the power of the digital universe in the hands of our customers wherever, whenever and however they want. We give our people the opportunity to inspire and lead teams, and work on projects that connect people, cities, businesses, and ideas. We want you to help us change the world, for the better. Diversity and inclusion Inclusion and valuing diversity of thought and experience are at the heart of our culture here at Colt. From day one, you'll be encouraged to be yourself because we believe that's what helps our people to thrive. We welcome people with diverse backgrounds and experiences, regardless of their gender identity or expression, sexual orientation, race, religion, disability, neurodiversity, age, marital status, pregnancy status, or place of birth. Most recently we have: Signed the UN Women Empowerment Principles which guide our Gender Action Plan Trained 60 (and growing) Colties to be Mental Health First Aiders Please speak with a member of our recruitment team if you require adjustments to our recruitment process to support you. For more information about our Inclusion and Diversity agenda, visit our DEI pages . Benefits Our benefits support you through all parts of life, for both physical and mental health. Flexible working hours and the option to work from home. Extensive induction program with experienced mentors and buddies. Opportunities for further development and educational opportunities. Global Family Leave Policy. Employee Assistance Program. Internal inclusion & diversity employee networks. A global network When you join Colt you become part of our global network. We are proud of our colleagues and the stories and experience they bring - take a look at 'Our People' site including our Empowered Women in Tech.
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. Capital One is open to hiring a Remote Employee for this opportunity What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. Capital One is open to hiring a Remote Employee for this opportunity What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. Capital One is open to hiring a Remote Employee for this opportunity What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. Capital One is open to hiring a Remote Employee for this opportunity What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
